A data warehouse is defined as a central repository that allows enterprises to store and consolidate business data extracted from multiple source systems for the task of historical and trend ...

Has the traditional data warehouse finally reached the end of its life? If so, what will follow it? Will it be a hybrid? We find out.

To build a data warehouse, data must first be extracted and transformed from an organization’s various sources. Then, the data must be loaded into the database in a structured format. Finally, an ETL ...

What is a data lake? Some mistakenly believe that a data lake is just the 2.0 version of a data warehouse. While they are similar, they are different tools that should be used for different purposes.

The early implementation of the cloud service is still on a traditional data warehouse architecture where storage is directly attached to compute.

In a new Q&A from The Register, host Tim Phillips talks to Geeta Banda of Google about how it is reimagining BigQuery as a ...

It’s felt obvious for some time that, as an industry, we’ve been trying to shove square data warehousing tools into round, data-driven application holes. But it wasn’t until I read ...

What is the future of data warehousing with relation to the cloud? This question was originally answered on Quora by Christopher Lynch.

Experts joined DBTA's webinar, Top Trends in Modern Data Architecture for 2024, to examine how the evolving world of data architecture can be harnessed to successfully meet growing demands amid a ...

A data lakehouse addresses these typical limitations of a data lake, as well as data warehouse architecture, by combining the best elements of data warehouses and data lakes to deliver significant ...